Pandas Profiling Report

Dataset statistics

Number of variables	40
Number of observations	8030
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	2.5 MiB
Average record size in memory	320.0 B

Variable types

Numeric	9
Categorical	31

Alerts

`Managed By_Ethiopia Field Office` has constant value "0.0"	Constant
`Managed By_Haiti Field Office` has constant value "0.0"	Constant
`Product Group_ACT` has constant value "0.0"	Constant
`Sub Classification_ACT` has constant value "0.0"	Constant
`Unit of Measure (Per Pack)` is highly correlated with `Unit Price`	High correlation
`Line Item Quantity` is highly correlated with `Line Item Value` and 3 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Pack Price` is highly correlated with `Unit Price`	High correlation
`Unit Price` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`Weight (Kilograms)` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Freight Cost (USD)` is highly correlated with `Line Item Quantity` and 2 other fields	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 2 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 3 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 3 other fields	High correlation
`Vendor INCO Term_DDP` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 3 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_ARV` is highly correlated with `Product Group_HRDT` and 1 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Product Group_ARV` and 1 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_Adult` is highly correlated with `Sub Classification_Pediatric`	High correlation
`Sub Classification_HIV test` is highly correlated with `Product Group_ARV` and 1 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM` and 1 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_Adult`	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Unit of Measure (Per Pack)` is highly correlated with `Unit Price` and 1 other fields	High correlation
`Line Item Quantity` is highly correlated with `Line Item Value` and 3 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 2 other fields	High correlation
`Pack Price` is highly correlated with `Unit Price`	High correlation
`Unit Price` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`Weight (Kilograms)` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Freight Cost (USD)` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 2 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 3 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 3 other fields	High correlation
`Vendor INCO Term_DDP` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 3 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_ARV` is highly correlated with `Product Group_HRDT` and 1 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Product Group_ARV` and 1 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_Adult` is highly correlated with `Sub Classification_Pediatric`	High correlation
`Sub Classification_HIV test` is highly correlated with `Product Group_ARV` and 1 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM` and 1 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Line Item Quantity` is highly correlated with `Line Item Value` and 2 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Pack Price` is highly correlated with `Unit Price`	High correlation
`Unit Price` is highly correlated with `Pack Price`	High correlation
`Weight (Kilograms)` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Freight Cost (USD)` is highly correlated with `Weight (Kilograms)`	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 1 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Fulfill Via_From RDC` and 3 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 3 other fields	High correlation
`Vendor INCO Term_DDP` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Fulfill Via_Direct Drop` and 2 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Fulfill Via_Direct Drop` and 3 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_ARV` is highly correlated with `Product Group_HRDT` and 1 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Product Group_ARV` and 1 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_Adult` is highly correlated with `Sub Classification_Pediatric`	High correlation
`Sub Classification_HIV test` is highly correlated with `Product Group_ARV` and 1 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM` and 1 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_Adult`	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`Vendor INCO Term_CIF` is highly correlated with `Sub Classification_ACT` and 3 other fields	High correlation
`Vendor INCO Term_FCA` is highly correlated with `Sub Classification_ACT` and 3 other fields	High correlation
`Vendor INCO Term_DAP` is highly correlated with `Sub Classification_ACT` and 3 other fields	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Sub Classification_ACT` and 4 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Sub Classification_ACT` and 5 other fields	High correlation
`Shipment Mode_Truck` is highly correlated with `Sub Classification_ACT` and 4 other fields	High correlation
`Sub Classification_ACT` is highly correlated with `Vendor INCO Term_CIF` and 29 other fields	High correlation
`Vendor INCO Term_DDP` is highly correlated with `Sub Classification_ACT` and 6 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Sub Classification_ACT` and 4 other fields	High correlation
`Vendor INCO Term_CIP` is highly correlated with `Sub Classification_ACT` and 3 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office` and 4 other fields	High correlation
`Product Group_ARV` is highly correlated with `Sub Classification_ACT` and 5 other fields	High correlation
`Shipment Mode_Ocean` is highly correlated with `Sub Classification_ACT` and 3 other fields	High correlation
`Managed By_Ethiopia Field Office` is highly correlated with `Vendor INCO Term_CIF` and 29 other fields	High correlation
`Product Group_ACT` is highly correlated with `Vendor INCO Term_CIF` and 29 other fields	High correlation
`Sub Classification_HIV test - Ancillary` is highly correlated with `Sub Classification_ACT` and 3 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Sub Classification_ACT` and 5 other fields	High correlation
`First Line Designation_Yes` is highly correlated with `Sub Classification_ACT` and 4 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `Sub Classification_ACT` and 6 other fields	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria` and 4 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `Sub Classification_ACT` and 7 other fields	High correlation
`Managed By_Haiti Field Office` is highly correlated with `Vendor INCO Term_CIF` and 29 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck` and 4 other fields	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `Sub Classification_ACT` and 7 other fields	High correlation
`Shipment Mode_Air Charter` is highly correlated with `Sub Classification_ACT` and 3 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Sub Classification_ACT` and 5 other fields	High correlation
`First Line Designation_No` is highly correlated with `Sub Classification_ACT` and 4 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `Sub Classification_ACT` and 7 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria` and 4 other fields	High correlation
`Sub Classification_Adult` is highly correlated with `Sub Classification_ACT` and 4 other fields	High correlation
`Vendor INCO Term_DDU` is highly correlated with `Sub Classification_ACT` and 3 other fields	High correlation
`df_index` is highly correlated with `Fulfill Via_Direct Drop` and 4 other fields	High correlation
`Unit of Measure (Per Pack)` is highly correlated with `Pack Price` and 3 other fields	High correlation
`Line Item Quantity` is highly correlated with `Line Item Value` and 4 other fields	High correlation
`Line Item Value` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Pack Price` is highly correlated with `Unit of Measure (Per Pack)` and 1 other fields	High correlation
`Unit Price` is highly correlated with `Unit of Measure (Per Pack)` and 6 other fields	High correlation
`Weight (Kilograms)` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Freight Cost (USD)` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Line Item Insurance (USD)` is highly correlated with `Line Item Quantity` and 3 other fields	High correlation
`Managed By_PMO - US` is highly correlated with `Managed By_South Africa Field Office`	High correlation
`Managed By_South Africa Field Office` is highly correlated with `Managed By_PMO - US`	High correlation
`Fulfill Via_Direct Drop` is highly correlated with `df_index` and 4 other fields	High correlation
`Fulfill Via_From RDC` is highly correlated with `df_index` and 4 other fields	High correlation
`Vendor INCO Term_DDP` is highly correlated with `df_index` and 4 other fields	High correlation
`Vendor INCO Term_EXW` is highly correlated with `df_index` and 3 other fields	High correlation
`Vendor INCO Term_N/A - From RDC` is highly correlated with `df_index` and 4 other fields	High correlation
`Shipment Mode_Air` is highly correlated with `Shipment Mode_Truck`	High correlation
`Shipment Mode_Truck` is highly correlated with `Shipment Mode_Air`	High correlation
`Product Group_ANTM` is highly correlated with `Sub Classification_Malaria`	High correlation
`Product Group_ARV` is highly correlated with `Unit Price` and 3 other fields	High correlation
`Product Group_HRDT` is highly correlated with `Unit Price` and 3 other fields	High correlation
`Product Group_MRDT` is highly correlated with `Sub Classification_Malaria`	High correlation
`Sub Classification_Adult` is highly correlated with `Unit of Measure (Per Pack)` and 2 other fields	High correlation
`Sub Classification_HIV test` is highly correlated with `Unit Price` and 2 other fields	High correlation
`Sub Classification_HIV test - Ancillary` is highly correlated with `Product Group_ARV` and 1 other fields	High correlation
`Sub Classification_Malaria` is highly correlated with `Product Group_ANTM` and 1 other fields	High correlation
`Sub Classification_Pediatric` is highly correlated with `Unit of Measure (Per Pack)` and 2 other fields	High correlation
`First Line Designation_No` is highly correlated with `First Line Designation_Yes`	High correlation
`First Line Designation_Yes` is highly correlated with `First Line Designation_No`	High correlation
`df_index` has unique values	Unique

Reproduction

Analysis started	2022-05-21 15:46:03.459696
Analysis finished	2022-05-21 15:46:25.305526
Duration	21.85 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

df_index
Real number (ℝ_≥0)

HIGH CORRELATION
UNIQUE

Distinct	8030
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5589.931756

Minimum	0
Maximum	10323
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	62.9 KiB

Quantile statistics

Minimum	0
5-th percentile	711.9
Q1	2729.25
median	6002.5
Q3	8273.75
95-th percentile	9914.55
Maximum	10323
Range	10323
Interquartile range (IQR)	5544.5

Descriptive statistics

Standard deviation	3046.016925
Coefficient of variation (CV)	0.5449112901
Kurtosis	-1.286295953
Mean	5589.931756
Median Absolute Deviation (MAD)	2671
Skewness	-0.1820781911
Sum	44887152
Variance	9278219.107
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1	< 0.1%
7589	1	< 0.1%
7602	1	< 0.1%
7601	1	< 0.1%
7600	1	< 0.1%
7599	1	< 0.1%
7598	1	< 0.1%
7597	1	< 0.1%
7596	1	< 0.1%
7595	1	< 0.1%
Other values (8020)	8020	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
9	1	< 0.1%
10	1	< 0.1%

Value	Count	Frequency (%)
10323	1	< 0.1%
10322	1	< 0.1%
10321	1	< 0.1%
10320	1	< 0.1%
10319	1	< 0.1%
10318	1	< 0.1%
10317	1	< 0.1%
10316	1	< 0.1%
10315	1	< 0.1%
10314	1	< 0.1%

Unit of Measure (Per Pack)
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	13
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.051315809

Minimum	3.218875825
Maximum	5.598421959
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	62.9 KiB

Quantile statistics

Minimum	3.218875825
5-th percentile	3.401197382
Q1	3.401197382
median	4.094344562
Q3	4.094344562
95-th percentile	5.480638923
Maximum	5.598421959
Range	2.379546134
Interquartile range (IQR)	0.6931471806

Descriptive statistics

Standard deviation	0.6047184472
Coefficient of variation (CV)	0.149264702
Kurtosis	0.362615847
Mean	4.051315809
Median Absolute Deviation (MAD)	0.4054651081
Skewness	0.8896652381
Sum	32532.06595
Variance	0.3656844003
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=13)

Value	Count	Frequency (%)
4.094344562	3937	49.0%
3.401197382	2502	31.2%
5.480638923	636	7.9%
4.787491743	398	5.0%
4.49980967	199	2.5%
4.605170186	98	1.2%
3.218875825	92	1.1%
5.192956851	74	0.9%
5.298317367	69	0.9%
4.430816799	17	0.2%
Other values (3)	8	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
3.218875825	92	1.1%
3.401197382	2502	31.2%
4.094344562	3937	49.0%
4.430816799	17	0.2%
4.49980967	199	2.5%
4.605170186	98	1.2%
4.787491743	398	5.0%
4.9698133	1	< 0.1%
5.075173815	1	< 0.1%
5.192956851	74	0.9%

Value	Count	Frequency (%)
5.598421959	6	0.1%
5.480638923	636	7.9%
5.298317367	69	0.9%
5.192956851	74	0.9%
5.075173815	1	< 0.1%
4.9698133	1	< 0.1%
4.787491743	398	5.0%
4.605170186	98	1.2%
4.49980967	199	2.5%
4.430816799	17	0.2%

Line Item Quantity
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4614
Distinct (%)	57.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	8.345260544

Minimum	2.397895273
Maximum	13.3061938
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	62.9 KiB

Quantile statistics

Minimum	2.397895273
5-th percentile	4.127134385
Q1	6.845081578
median	8.616585833
Q3	10.14844149
95-th percentile	11.51292546
Maximum	13.3061938
Range	10.90829852
Interquartile range (IQR)	3.303359908

Descriptive statistics

Standard deviation	2.266866612
Coefficient of variation (CV)	0.2716352114
Kurtosis	-0.4994622707
Mean	8.345260544
Median Absolute Deviation (MAD)	1.663229737
Skewness	-0.4526597657
Sum	67012.44217
Variance	5.138684237
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
9.210340372	88	1.1%
6.907755279	64	0.8%
9.903487553	63	0.8%
10.81977828	60	0.7%
4.605170186	56	0.7%
7.60090246	53	0.7%
8.517193191	52	0.6%
8.006367568	52	0.6%
8.29404964	50	0.6%
11.51292546	49	0.6%
Other values (4604)	7443	92.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2.397895273	15	0.2%
2.48490665	16	0.2%
2.564949357	9	0.1%
2.63905733	9	0.1%
2.708050201	7	0.1%
2.772588722	11	0.1%
2.833213344	8	0.1%
2.890371758	8	0.1%
2.944438979	15	0.2%
2.995732274	25	0.3%

Value	Count	Frequency (%)
13.3061938	1	< 0.1%
13.22707828	1	< 0.1%
13.15192218	3	< 0.1%
13.15100137	1	< 0.1%
13.03907089	1	< 0.1%
12.99453001	1	< 0.1%
12.90411035	1	< 0.1%
12.89921983	2	< 0.1%
12.79385931	1	< 0.1%
12.78514366	1	< 0.1%

Line Item Value
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	7252
Distinct (%)	90.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	10.3121574

Minimum	4.521571162
Maximum	15.56795689
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	62.9 KiB

Quantile statistics

Minimum	4.521571162
5-th percentile	6.317400115
Q1	8.707511025
median	10.49266214
Q3	12.10065612
95-th percentile	13.56684241
Maximum	15.56795689
Range	11.04638573
Interquartile range (IQR)	3.393145099

Descriptive statistics

Standard deviation	2.225946177
Coefficient of variation (CV)	0.2158564974
Kurtosis	-0.6986059651
Mean	10.3121574
Median Absolute Deviation (MAD)	1.680399218
Skewness	-0.2933036894
Sum	82806.6239
Variance	4.954836381
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
12.20607265	25	0.3%
9.680344001	11	0.1%
8.070906089	10	0.1%
13.30551792	9	0.1%
10.04763984	9	0.1%
12.52661873	8	0.1%
10.77978928	7	0.1%
7.937374696	7	0.1%
12.08728911	7	0.1%
6.733401892	6	0.1%
Other values (7242)	7931	98.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
4.521571162	1	< 0.1%
4.695924549	1	< 0.1%
4.698660529	1	< 0.1%
4.711690029	1	< 0.1%
4.749443675	1	< 0.1%
4.766012711	1	< 0.1%
4.80073697	1	< 0.1%
4.804021045	1	< 0.1%
4.817050545	1	< 0.1%
4.819474789	1	< 0.1%

Value	Count	Frequency (%)
15.56795689	1	< 0.1%
15.48884138	1	< 0.1%
15.45258596	1	< 0.1%
15.41676346	1	< 0.1%
15.25738856	1	< 0.1%
15.20529881	1	< 0.1%
15.18488254	1	< 0.1%
15.17751223	2	< 0.1%
15.15049847	1	< 0.1%
15.09294969	1	< 0.1%

Pack Price
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	980
Distinct (%)	12.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.966913459

Minimum	0.08157998699
Maximum	4.24563401
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	62.9 KiB

Quantile statistics

Minimum	0.08157998699
5-th percentile	0.6418538862
Q1	1.235458844
median	2.014903021
Q3	2.519308077
95-th percentile	3.506457892
Maximum	4.24563401
Range	4.164054023
Interquartile range (IQR)	1.283849232

Descriptive statistics

Standard deviation	0.8877803672
Coefficient of variation (CV)	0.4513571062
Kurtosis	-0.6221087941
Mean	1.966913459
Median Absolute Deviation (MAD)	0.6411874416
Skewness	0.1424767998
Sum	15794.31508
Variance	0.7881539804
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2.4176979	139	1.7%
2.995732274	109	1.4%
0.6678293726	91	1.1%
2.170195905	91	1.1%
0.7419373447	89	1.1%
0.8919980393	87	1.1%
0.8153648133	87	1.1%
2.111424588	81	1.0%
2.043814364	76	0.9%
1.945910149	74	0.9%
Other values (970)	7106	88.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.08157998699	4	< 0.1%
0.0953101798	2	< 0.1%
0.1310282624	2	< 0.1%
0.1570037488	1	< 0.1%
0.1823215568	1	< 0.1%
0.2231435513	24	0.3%
0.2623642645	21	0.3%
0.2776317366	5	0.1%
0.292669614	3	< 0.1%
0.3001045925	3	< 0.1%

Value	Count	Frequency (%)
4.24563401	1	< 0.1%
4.244343779	3	< 0.1%
4.233961567	4	< 0.1%
4.224202549	2	< 0.1%
4.204692619	2	< 0.1%
4.200954297	1	< 0.1%
4.198704578	15	0.2%
4.185859671	3	< 0.1%
4.184794465	1	< 0.1%
4.177919486	1	< 0.1%

Unit Price
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	127
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-2.071966746

Minimum	-4.605170186
Maximum	0.5306282511
Zeros	1
Zeros (%)	< 0.1%
Negative	7959
Negative (%)	99.1%
Memory size	62.9 KiB

Quantile statistics

Minimum	-4.605170186
5-th percentile	-4.605170186
Q1	-2.813410717
median	-1.966112856
Q3	-1.30933332
95-th percentile	-0.2876820725
Maximum	0.5306282511
Range	5.135798437
Interquartile range (IQR)	1.504077397

Descriptive statistics

Standard deviation	1.099054047
Coefficient of variation (CV)	-0.5304400028
Kurtosis	-0.04970734499
Mean	-2.071966746
Median Absolute Deviation (MAD)	0.7282385004
Skewness	-0.4005709989
Sum	-16637.89297
Variance	1.207919798
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-3.218875825	690	8.6%
-4.605170186	482	6.0%
-2.120263536	449	5.6%
-1.966112856	412	5.1%
-2.207274913	358	4.5%
-1.832581464	337	4.2%
-2.995732274	332	4.1%
-1.660731207	315	3.9%
-2.040220829	304	3.8%
-1.897119985	274	3.4%
Other values (117)	4077	50.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-4.605170186	482	6.0%
-3.912023005	118	1.5%
-3.506557897	229	2.9%
-3.218875825	690	8.6%
-2.995732274	332	4.1%
-2.813410717	266	3.3%
-2.659260037	222	2.8%
-2.525728644	113	1.4%
-2.407945609	148	1.8%
-2.302585093	187	2.3%

Value	Count	Frequency (%)
0.5306282511	1	< 0.1%
0.5187937934	15	0.2%
0.4700036292	1	< 0.1%
0.4637340162	1	< 0.1%
0.4446858213	2	< 0.1%
0.4121096508	1	< 0.1%
0.4054651081	5	0.1%
0.3435897044	1	< 0.1%
0.3148107398	1	< 0.1%
0.2776317366	1	< 0.1%

Weight (Kilograms)
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3544
Distinct (%)	44.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.08486449

Minimum	1.504077397
Maximum	11.38724886
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	62.9 KiB

Quantile statistics

Minimum	1.504077397
5-th percentile	3.518212227
Q1	5.749392986
median	7.388018549
Q3	8.56712556
95-th percentile	9.865419548
Maximum	11.38724886
Range	9.88317146
Interquartile range (IQR)	2.817732574

Descriptive statistics

Standard deviation	1.95982352
Coefficient of variation (CV)	0.2766211722
Kurtosis	-0.4164495317
Mean	7.08486449
Median Absolute Deviation (MAD)	1.363455938
Skewness	-0.449578562
Sum	56891.46185
Variance	3.840908229
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3.828641396	28	0.3%
2.197224577	22	0.3%
4.33073334	18	0.2%
4.718498871	18	0.2%
3.401197382	17	0.2%
6.045005314	17	0.2%
1.791759469	16	0.2%
3.688879454	15	0.2%
4.787491743	15	0.2%
3.583518938	14	0.2%
Other values (3534)	7850	97.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1.504077397	2	< 0.1%
1.609437912	11	0.1%
1.704748092	2	< 0.1%
1.791759469	16	0.2%
1.871802177	2	< 0.1%
1.945910149	9	0.1%
2.014903021	5	0.1%
2.079441542	11	0.1%
2.140066163	1	< 0.1%
2.197224577	22	0.3%

Value	Count	Frequency (%)
11.38724886	1	< 0.1%
11.37453658	2	< 0.1%
11.35191129	1	< 0.1%
11.31614386	3	< 0.1%
11.31247252	4	< 0.1%
11.25712958	1	< 0.1%
11.22902291	3	< 0.1%
11.1978722	3	< 0.1%
11.15780645	9	0.1%
11.14115139	2	< 0.1%

Freight Cost (USD)
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4994
Distinct (%)	62.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	8.72762346

Minimum	2.664446564
Maximum	12.17882189
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	62.9 KiB

Quantile statistics

Minimum	2.664446564
5-th percentile	6.709567953
Q1	7.910472816
median	8.802870369
Q3	9.596747016
95-th percentile	10.65349227
Maximum	12.17882189
Range	9.51437533
Interquartile range (IQR)	1.6862742

Descriptive statistics

Standard deviation	1.228565381
Coefficient of variation (CV)	0.1407674594
Kurtosis	0.2529671375
Mean	8.72762346
Median Absolute Deviation (MAD)	0.8327102866
Skewness	-0.2802643972
Sum	70082.81638
Variance	1.509372895
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
9.183595906	37	0.5%
8.723748719	27	0.3%
8.915405394	26	0.3%
8.899707602	19	0.2%
9.142221047	19	0.2%
9.502865199	18	0.2%
9.746248776	16	0.2%
9.71308342	15	0.2%
9.928147482	15	0.2%
8.617962986	14	0.2%
Other values (4984)	7824	97.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2.664446564	2	< 0.1%
2.874693945	1	< 0.1%
3.104138147	1	< 0.1%
3.374511116	3	< 0.1%
3.401197382	1	< 0.1%
3.417398761	1	< 0.1%
3.745968421	1	< 0.1%
3.871201011	1	< 0.1%
4.144245221	1	< 0.1%
4.454347296	1	< 0.1%

Value	Count	Frequency (%)
12.17882189	2	< 0.1%
11.99357763	13	0.2%
11.89717143	1	< 0.1%
11.8963825	1	< 0.1%
11.79727903	4	< 0.1%
11.78507866	1	< 0.1%
11.77408316	3	< 0.1%
11.75418772	1	< 0.1%
11.7308622	1	< 0.1%
11.7275932	4	< 0.1%

Line Item Insurance (USD)
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	5927
Distinct (%)	73.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.819218077

Minimum	-1.897119985
Maximum	8.950071111
Zeros	2
Zeros (%)	< 0.1%
Negative	507
Negative (%)	6.3%
Memory size	62.9 KiB

Quantile statistics

Minimum	-1.897119985
5-th percentile	-0.2357223335
Q1	2.199721342
median	4.036803718
Q3	5.588885891
95-th percentile	7.091837365
Maximum	8.950071111
Range	10.8471911
Interquartile range (IQR)	3.389164548

Descriptive statistics

Standard deviation	2.246860513
Coefficient of variation (CV)	0.5883038013
Kurtosis	-0.6549805057
Mean	3.819218077
Median Absolute Deviation (MAD)	1.672911108
Skewness	-0.3284660099
Sum	30668.32116
Variance	5.048382164
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-1.272965676	13	0.2%
5.799092654	13	0.2%
-0.8675005677	13	0.2%
-1.386294361	13	0.2%
-1.078809661	12	0.1%
1.633154439	11	0.1%
-0.6161861394	11	0.1%
-0.8209805521	11	0.1%
-0.04082199452	11	0.1%
-1.237874356	10	0.1%
Other values (5917)	7912	98.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1.897119985	4	< 0.1%
-1.832581464	2	< 0.1%
-1.771956842	3	< 0.1%
-1.714798428	6	0.1%
-1.660731207	5	0.1%
-1.609437912	4	< 0.1%
-1.560647748	2	< 0.1%
-1.514127733	6	0.1%
-1.46967597	6	0.1%
-1.427116356	9	0.1%

Value	Count	Frequency (%)
8.950071111	1	< 0.1%
8.687816591	1	< 0.1%
8.625744411	1	< 0.1%
8.608701608	1	< 0.1%
8.572446236	1	< 0.1%
8.562321421	1	< 0.1%
8.549135558	1	< 0.1%
8.545780648	2	< 0.1%
8.5366232	1	< 0.1%
8.525897201	1	< 0.1%

Managed By_Ethiopia Field Office
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	8030

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8030	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8030	100.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Managed By_Haiti Field Office
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	8030

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8030	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8030	100.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Managed By_PMO - US
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

1.0	7982
0.0	48

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	7982	99.4%
0.0	48	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	7982	99.4%
0.0	48	0.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Managed By_South Africa Field Office
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	7982
1.0	48

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	7982	99.4%
1.0	48	0.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	7982	99.4%
1.0	48	0.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Fulfill Via_Direct Drop
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	5070
1.0	2960

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	5070	63.1%
1.0	2960	36.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	5070	63.1%
1.0	2960	36.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Fulfill Via_From RDC
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

1.0	5070
0.0	2960

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
1.0	5070	63.1%
0.0	2960	36.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	5070	63.1%
0.0	2960	36.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_CIF
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	8029
1.0	1

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8029	> 99.9%
1.0	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8029	> 99.9%
1.0	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_CIP
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	7795
1.0	235

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	7795	97.1%
1.0	235	2.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	7795	97.1%
1.0	235	2.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_DAP
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	8024
1.0	6

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8024	99.9%
1.0	6	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8024	99.9%
1.0	6	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_DDP
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	6918
1.0	1112

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	6918	86.2%
1.0	1112	13.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	6918	86.2%
1.0	1112	13.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_DDU
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	8024
1.0	6

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8024	99.9%
1.0	6	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8024	99.9%
1.0	6	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_EXW
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	6646
1.0	1384

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	6646	82.8%
1.0	1384	17.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	6646	82.8%
1.0	1384	17.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_FCA
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	7814
1.0	216

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	7814	97.3%
1.0	216	2.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	7814	97.3%
1.0	216	2.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Vendor INCO Term_N/A - From RDC
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

1.0	5070
0.0	2960

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
1.0	5070	63.1%
0.0	2960	36.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	5070	63.1%
0.0	2960	36.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Air
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

1.0	4262
0.0	3768

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	4262	53.1%
0.0	3768	46.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	4262	53.1%
0.0	3768	46.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Air Charter
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	7395
1.0	635

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	7395	92.1%
1.0	635	7.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	7395	92.1%
1.0	635	7.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Ocean
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	7663
1.0	367

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	7663	95.4%
1.0	367	4.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	7663	95.4%
1.0	367	4.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Shipment Mode_Truck
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	5548
1.0	2482

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	5548	69.1%
1.0	2482	30.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	5548	69.1%
1.0	2482	30.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_ACT
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	8030

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8030	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8030	100.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_ANTM
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	8025
1.0	5

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8025	99.9%
1.0	5	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8025	99.9%
1.0	5	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_ARV
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

1.0	7842
0.0	188

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	7842	97.7%
0.0	188	2.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	7842	97.7%
0.0	188	2.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_HRDT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	7853
1.0	177

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	7853	97.8%
1.0	177	2.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	7853	97.8%
1.0	177	2.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Product Group_MRDT
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	8024
1.0	6

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8024	99.9%
1.0	6	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8024	99.9%
1.0	6	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_ACT
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	8030

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8030	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8030	100.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_Adult
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

1.0	6169
0.0	1861

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	1.0
4th row	1.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
1.0	6169	76.8%
0.0	1861	23.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	6169	76.8%
0.0	1861	23.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_HIV test
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	7881
1.0	149

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	7881	98.1%
1.0	149	1.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	7881	98.1%
1.0	149	1.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_HIV test - Ancillary
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	8002
1.0	28

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8002	99.7%
1.0	28	0.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8002	99.7%
1.0	28	0.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_Malaria
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	8019
1.0	11

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	8019	99.9%
1.0	11	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	8019	99.9%
1.0	11	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Sub Classification_Pediatric
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	6357
1.0	1673

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	6357	79.2%
1.0	1673	20.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	6357	79.2%
1.0	1673	20.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

First Line Designation_No
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

0.0	5245
1.0	2785

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	0.0

Common Values

Value	Count	Frequency (%)
0.0	5245	65.3%
1.0	2785	34.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	5245	65.3%
1.0	2785	34.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

First Line Designation_Yes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	62.9 KiB

1.0	5245
0.0	2785

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	5245	65.3%
0.0	2785	34.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	5245	65.3%
0.0	2785	34.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	df_index	Unit of Measure (Per Pack)	Line Item Quantity	Line Item Value	Pack Price	Unit Price	Weight (Kilograms)	Freight Cost (USD)	Line Item Insurance (USD)	Managed By_PMO - US	Fulfill Via_Direct Drop	Vendor INCO Term_CIP	Vendor INCO Term_DDU	Vendor INCO Term_EXW	Shipment Mode_Air	Product Group_ARV	Product Group_HRDT	Sub Classification_Adult	Sub Classification_HIV test	Sub Classification_Pediatric	First Line Designation_No	First Line Designation_Yes
0	0	3.401197	2.944439	6.311735	3.367296	-0.030459	2.564949	6.659730	-0.267879	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0	1.0	0.0	0.0	1.0
1	1	5.480639	6.907755	8.732305	1.824549	-3.506558	5.880533	8.416599	2.345645	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0
2	3	4.094345	10.370988	11.754779	1.383791	-2.659260	7.525640	9.680785	5.330494	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0
3	4	4.094345	10.545341	11.708492	1.163151	-2.995732	8.934587	10.724370	5.343840	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0
4	5	5.480639	6.030685	7.707782	1.677097	-3.912023	6.222576	8.686163	1.291984	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0
5	6	4.499810	4.905275	8.383433	3.478158	-1.021651	5.793014	7.331754	1.512927	1.0	1.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	0.0	1.0	0.0	1.0
6	7	4.094345	9.721186	11.015913	1.294727	-2.813411	7.298445	8.734304	4.111693	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0
7	8	4.094345	5.609472	6.277301	0.667829	-3.506558	6.171701	8.489028	-0.470004	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	1.0	0.0	0.0	1.0	0.0
8	9	4.787492	7.937375	11.653383	3.716008	-1.078810	6.466145	9.176516	5.216945	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0
9	10	4.787492	7.937375	11.653383	3.716008	-1.078810	6.466145	9.176516	5.216945	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0	0.0	0.0	1.0

Last rows

	df_index	Unit of Measure (Per Pack)	Line Item Quantity	Line Item Value	Pack Price	Unit Price	Weight (Kilograms)	Freight Cost (USD)	Line Item Insurance (USD)	Managed By_PMO - US	Fulfill Via_From RDC	Vendor INCO Term_N/A - From RDC	Shipment Mode_Air	Shipment Mode_Air Charter	Shipment Mode_Truck	Product Group_ARV	Sub Classification_Adult	Sub Classification_Pediatric	First Line Designation_No	First Line Designation_Yes
8020	10314	4.094345	9.243775	10.524709	1.280934	-2.813411	8.747511	9.737492	3.644666	1.0	1.0	1.0	0.0	1.0	0.0	1.0	0.0	1.0	1.0	0.0
8021	10315	4.787492	11.156251	14.081560	2.925310	-1.832581	9.628919	10.172751	7.201417	1.0	1.0	1.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0
8022	10316	4.094345	9.615805	11.490680	1.874874	-2.207275	7.344073	8.134468	4.745888	1.0	1.0	1.0	0.0	1.0	0.0	1.0	1.0	0.0	0.0	1.0
8023	10317	3.401197	8.813438	9.951271	1.137833	-2.302585	8.729559	10.763876	3.206398	1.0	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	0.0
8024	10318	4.094345	12.231950	13.512884	1.280934	-2.813411	10.161226	10.738819	6.768102	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	1.0	0.0
8025	10319	4.094345	12.023177	13.304111	1.280934	-2.813411	10.161226	10.738819	6.559318	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	1.0	0.0
8026	10320	4.094345	9.955700	11.830575	1.874874	-2.207275	8.395252	9.597975	5.085805	1.0	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	1.0	0.0
8027	10321	3.401197	13.151001	15.452586	2.301585	-1.108663	11.045040	11.106081	8.572446	1.0	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	1.0	0.0
8028	10322	4.094345	9.767954	11.642829	1.874874	-2.207275	7.238497	8.208602	4.898064	1.0	1.0	1.0	0.0	0.0	1.0	1.0	1.0	0.0	0.0	1.0
8029	10323	4.094345	10.508869	11.197003	0.688135	-3.506558	9.483568	9.364870	4.452252	1.0	1.0	1.0	0.0	0.0	1.0	1.0	0.0	1.0	1.0	0.0

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script